Efficiency score from data envelopment analysis can predict the future onset of hypertension and dyslipidemia: A cohort study.
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ABSTRACT:
SUBMITTER: Nakamura S
PROVIDER: S-EPMC6841950 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:The traditional data envelopment analysis (DEA) literatures generally concentrated on the efficiency evaluation of single decision making unit (DMU). However, in many practical problems, the decision makers are required to choose a number of DMUs instead of a single one from the DMUs set. Therefore, it is necessary to study the combinatorial efficiency evaluation problem which can be illustrated as a knapsack problem naturally. It is indicated that the basic model proposed by Cook and Green may have some drawbacks and a modified model, which is combined with the super efficiency model, is proposed in this paper. What is more, our proposed model is more persuasive to the decision makers because it is able to provide a unique best combination of DMUs. An adapted local search algorithm is developed as a solver of this problem. Finally, numerical examples are provided to examine the validity of our proposed model and the adapted local search algorithm.
| S-EPMC4119746 | biostudies-other
Project description:RNA was isolated from plasma of 20 healthy patients and 20 patients with acute pulmonary embolism. Dysregulated microRNA patterns were screened in these samples
2023-11-20 | GSE247365 | GEO
Project description:OBJECTIVE:This study aims to estimate the technical efficiency of health systems in Asia. SETTINGS:The study was conducted in Asian countries. METHODS:We applied an output-oriented data envelopment analysis (DEA) approach to estimate the technical efficiency of the health systems in Asian countries. The DEA model used per-capita health expenditure (all healthcare resources as a proxy) as input variable and cross-country comparable health outcome indicators (eg, healthy life expectancy at birth and infant mortality per 1000 live births) as output variables. Censored Tobit regression and smoothed bootstrap models were used to observe the associated factors with the efficiency scores. A sensitivity analysis was performed to assess the consistency of these efficiency scores. RESULTS:The main findings of this paper demonstrate that about 91.3% (42 of 46 countries) of the studied Asian countries were inefficient with respect to using healthcare system resources. Most of the efficient countries belonged to the high-income group (Cyprus, Japan, and Singapore) and only one country belonged to the lower middle-income group (Bangladesh). Through improving health system efficiency, the studied high-income, upper middle-income, low-income and lower middle-income countries can improve health system outcomes by 6.6%, 8.6% and 8.7%, respectively, using the existing level of resources. Population density, bed density, and primary education completion rate significantly influenced the efficiency score. CONCLUSION:The results of this analysis showed inefficiency of the health systems in most of the Asian countries and imply that many countries may improve their health system efficiency using the current level of resources. The identified inefficient countries could pay attention to benchmarking their health systems within their income group or other within similar types of health systems.
| S-EPMC6475137 | biostudies-literature
Project description:BackgroundIn order to measure and analyse the technical efficiency of district hospitals in Ghana, the specific objectives of this study were to (a) estimate the relative technical and scale efficiency of government, mission, private and quasi-government district hospitals in Ghana in 2005; (b) estimate the magnitudes of output increases and/or input reductions that would have been required to make relatively inefficient hospitals more efficient; and (c) use Tobit regression analysis to estimate the impact of ownership on hospital efficiency.MethodsIn the first stage, we used data envelopment analysis (DEA) to estimate the efficiency of 128 hospitals comprising of 73 government hospitals, 42 mission hospitals, 7 quasi-government hospitals and 6 private hospitals. In the second stage, the estimated DEA efficiency scores are regressed against hospital ownership variable using a Tobit model. This was a retrospective study.ResultsIn our DEA analysis, using the variable returns to scale model, out of 128 district hospitals, 31 (24.0%) were 100% efficient, 25 (19.5%) were very close to being efficient with efficiency scores ranging from 70% to 99.9% and 71 (56.2%) had efficiency scores below 50%. The lowest-performing hospitals had efficiency scores ranging from 21% to 30%.Quasi-government hospitals had the highest mean efficiency score (83.9%) followed by public hospitals (70.4%), mission hospitals (68.6%) and private hospitals (55.8%). However, public hospitals also got the lowest mean technical efficiency scores (27.4%), implying they have some of the most inefficient hospitals.Regarding regional performance, Northern region hospitals had the highest mean efficiency score (83.0%) and Volta Region hospitals had the lowest mean score (43.0%).From our Tobit regression, we found out that while quasi-government ownership is positively associated with hospital technical efficiency, private ownership negatively affects hospital efficiency.ConclusionsIt would be prudent for policy-makers to examine the least efficient hospitals to correct widespread inefficiency. This would include reconsidering the number of hospitals and their distribution, improving efficiency and reducing duplication by closing or scaling down hospitals with efficiency scores below a certain threshold. For private hospitals with inefficiency related to large size, there is a need to break down such hospitals into manageable sizes.
| S-EPMC4108084 | biostudies-literature
Project description:For patients with diabetes, annual preventive care is essential to reduce the risk of complications. Local healthcare resources affect the utilization of diabetes preventive care. Our objectives were to evaluate the relative efficiency of counties in providing diabetes preventive care and explore potential to improve efficiencies. The study setting is public and private healthcare providers in US counties with available data. County-level demographics were extracted from the Area Health Resources File using data from 2010 to 2013, and individual-level information of diabetes preventive service use was obtained from the 2010 Behavioral Risk Factor Surveillance System. 1112 US counties were analyzed. Cluster analysis was used to place counties into three similar groups in terms of economic wellbeing and population characteristics. Group 1 consisted of metropolitan counties with prosperous or comfortable economic levels. Group 2 mostly consisted of non-metropolitan areas between distress and mid-tier levels, while Group 3 were mostly prosperous or comfortable counties in metropolitan areas. We used data enveopement analysis to assess efficiencies within each group. The majority of counties had modest efficiency in providing diabetes preventive care; 36 counties (57.1%), 345 counties (61.1%), and 263 counties (54.3%) were inefficient (efficiency scores < 1) in Group 1, Group 2, and Group 3, respectively. For inefficient counties, foot and eye exams were often identified as sources of inefficiency. Available health professionals in some counties were not fully utilized to provide diabetes preventive care. Identifying benchmarking targets from counties with similar resources can help counties and policy makers develop actionable strategies to improve performance.
| S-EPMC8612454 | biostudies-literature
Project description:OBJECTIVE:In this study, we assess the performance of public hospitals in Saudi Arabia. We detect the sources of inefficiency and estimate the optimal levels of the resources that provide the current level of health services. We enrich our analysis by employing locations and capacities of the hospitals. DESIGN:We employ data envelopment analysis (DEA) to measure the technical efficiency of 91 public hospitals. We apply the input-oriented Charnes, Cooper and Rhodes, and Banker, Charne, Cooper models under Constant and Variable Returns-to-Scale. The assessment includes four inputs, and six output variables taken from the Ministry of Health databases for 2017. We conducted the assessment via PIM-DEA V.3.2 software. SETTING:Ministry of health-affiliated hospitals in the Kingdom of Saudi Arabia. RESULTS:Findings identified 75.8% (69 of 91) of public hospitals as technically inefficient. The average efficiency score was 0.76, indicating that hospitals could have reduced their inputs by 24% without reduction in health service provision. Small hospitals (efficiency score 0.79) were more efficient than medium-sized and large hospitals. Hospitals in the central region were more efficient (efficiency score 0.83), than those located in other geographical locations. More than half of the hospitals (62.6%) were operating suboptimally in terms of the scale efficiency, implying that to improve efficiency, they need to alter their production capacity. Performance analysis identified overuse of physician's numbers and shortage of health services production, as major causes of inefficiency. CONCLUSION:Most hospitals were technically inefficient and operating at suboptimal scale size and indicate that many hospitals may improve their performance through efficient utilisation of health resources to provide the current level of health services. Changes in the production capacity are required, to facilitate optimal use of medical capacity. The inefficient hospitals could benefit from these findings to benchmarking their system and performance in light of the efficient hospital within their capacity and geographical location.
| S-EPMC7045210 | biostudies-literature
Project description:Environmental pollution and the associated societal health issues have attracted recent research attention. While most research has focused on the effect of air pollution on human health and local economies, few articles have discussed the environment, health, and economic development in in an integrated analysis. This paper used a Dynamic Network SBM Model to evaluate production and health efficiencies in Chinese cities and found that the production efficiency scores were slightly higher than the health efficiency scores, with the two-stage efficiency scores in most cities having significant fluctuations. Labor, fixed assets, energy, GDP, and lung disease and mortality reduction efficiencies in the first stage were generally high; however, the medical input efficiencies in the second stage were low, indicating that there was there significant room for improvement in many cities.
| S-EPMC6163775 | biostudies-literature
Project description:IntroductionOxidative stress plays a key role in the pathophysiology of hypertension development. The oxidative balance score (OBS) comprises dietary and lifestyle pro- and anti-oxidant components and reflects the overall oxidative stress burden. We aimed to evaluate the association between the OBS and new-onset hypertension (HTN) using large, community-based, prospective Korean cohort data.MethodsAmong 10,030 participants aged 40-69 years included in the Korean Genome and Epidemiology Study, the data of 5,181 participants were analyzed. The hazard ratio (HR) and 95% confidence interval (CI) for new-onset HTN according to sex-specific OBS quartile groups were calculated using univariable and multivariable Cox proportional hazard regression analyses.ResultsDuring the mean 13.6-year follow-up period, 1,157 men and 1,196 women developed new-onset HTN. Compared to the Q1 group, the adjusted HRs (95%CI) for new-onset HTN in the Q2, Q3, and Q4 groups were 0.96 (0.82-1.16), 0.85 (0.72-0.99), and 0.71 (0.59-0.86) in men and 0.81 (0.69-0.95), 0.81(0.68-0.95), and 0.70 (0.57-0.84) in women, respectively.DiscussionIndividuals with high OBS are at lower risk of developing HTN. This study suggests that a healthy lifestyle and antioxidant rich diet could be a preventive strategy for HTN.
| S-EPMC9798298 | biostudies-literature
Project description:ObjectiveWith escalating health expenditures and increasing health needs, improving health system performance has become imperative in China and internationally. The objective of this study is to examine the efficiency of China's health system and to understand the underlying causes of the variation in efficiency across provinces.SettingA system-wide perspective is adopted, focusing on performance in maternal health, child health and non-communicable diseases (NCDs) in the 31 provinces of mainland China during 2015.MethodsAnalyses were performed using bootstrapping data envelopment technique. Health outcomes were measured by infant survival rates, maternal survival rates and healthy life years calculated only considering NCDs. Health inputs were measured using health expenditure, and density of medical personnel and hospital beds. The model also examined the impact of environmental factors on health system efficiency.ResultsDue to wide-spread scale inefficiency in the country, the average bias-corrected overall technical efficiency (OTE) was 0.8022 (95% CI values ranging from 0.7251 to 0.8492). Socioeconomic status, hospitalisation rate and share of out-of-pocket expenditures were significant determinants of OTE. Nearly 60% of the provinces operated at a decreasing return to scale, meaning that a gain in efficiency could be achieved only through downsizing the scale of operation.ConclusionsGiven the pervasive nature of diminishing returns across provinces, health policy makers must explore the optimum operational scale which is people-centred and focused on prevention, rather than on treatment, of diseases. Moreover, due consideration should be afforded to social determinants of health and health financing arrangements to complement health-sector based reforms and meet the ambitious goals of the Healthy China 2030 Plan.
| S-EPMC6686990 | biostudies-literature
Project description:BackgroundPeople in Taiwan enjoy comprehensive National Health Insurance coverage. However, under the global budget constraint, hospitals encounter enormous challenges. This study was designed to examine Taiwan medical centers' efficiency and factors that influence it.MethodsWe obtained data from open sources of government routine publications and hospitals disclosed by law to the National Health Insurance Administration, Ministry of Health and Welfare, Taiwan. The dynamic data envelopment analysis (DDEA) model was adopted to estimate all medical centers' efficiencies during 2015-2018. Beta regression models were used to model the efficiency level obtained from the DDEA model. We applied an input-oriented approach under both the constant returns-to-scale (CRS) and variable returns-to-scale (VRS) assumptions to estimate efficiency.ResultsThe findings indicated that 68.4% (13 of 19) of medical centers were inefficient according to scale efficiency. The mean efficiency scores of all medical centers during 2015-2018 under the CRS, VRS, and Scale were 0.85, 0.930, and 0.95,respectively. Regression results showed that an increase in the population less than 14 years of age, assets, nurse-patient ratio and bed occupancy rate could increase medical centers' efficiency. The rate of emergency return within 3-day and patient self-pay revenues were associated significantly with reduced hospital efficiency (p < 0.05). The result also showed that the foundation owns medical center has the highest efficiency than other ownership hospitals.ConclusionsThe study results provide information for hospital managers to consider ways they could adjust available resources to achieve high efficiency.
| S-EPMC8976980 | biostudies-literature